I used Mplus to test a SEM model of the relation between socioeconomic status (SES) and smoking relapse. SES and the mediators are latent variables and smoking relapse is binary. Relapse was coded as a categorical variable. It is my understanding that Mplus is appropriate for this type of model. However, a reviewer made this comment "One important remaining issue, is the model interpretation. Given that the outcome measure (i.e., smoking status) is binary, the output of the model estimation, especially in regards to the dependent variable, has been interpreted as if the dependent variable was continuous. This is inappropriate. It does not appear that Mplus can estimate such a model (i.e., latent variable models with a binary dependent variable) within the latent variable framework. Clarification is needed."
I will cite the Mplus manual in my response to the reviewer, but are there any other citations that I can use to defend using Mplus to analyze this data?
If smoking status was put on the CATEGORICAL list, then as a dependent variable a probit regression is estimated using weighted least squares estimation and a logistic regression is estimated using maximum likelihood estimation. If you want further information, send the full output from the analysis and your license number to firstname.lastname@example.org.
Is it possible to run a multigroup model with a latent interaction and a dichotomous outcome in one model? My predictor(IV) and moderator is a latent variable (6 indicators each) and my outcome (DV) is dichotomous and I want to compare this interaction model by racial group. It seems I can run a model that has latent interaction and dichotomous outcome but once I try to test for multigroup comparison I get a warning. If this is possible could you please guide me to the codes for this type of model?